利用李雅普诺夫指数和熵估计对过程变异性的敏感性

E. A. Ramos, Ricardo Reis
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引用次数: 0

摘要

晶体管的技术缩放使它们更容易受到故障的影响,例如由于辐射效应和工艺可变性造成的故障。与工艺变异性相关的故障可能导致电路在其规范范围外运行。在大多数情况下,模拟用于分析这种效应,但模拟具有很高的计算成本。这项工作旨在通过李雅普诺夫指数和电路熵使用数学混沌理论来分析估计由制造过程的可变性引起的影响,从而产生一种方法,可以估计功率,延迟和功率延迟积(PDP)的可变性,其精度相当于基于仿真的方法,但平均速度快300倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Lyapunov Exponents and Entropy to Estimate Sensitivity to Process Variability
The technology scaling of transistors makes them more susceptible to faults, such as those due to radiation effects and process variability. Faults related to process variability can cause circuits to operate outside their specification ranges. In most cases, simulations are used to analyze such effects, but simulations have high computational costs. This work aims to use the Mathematical Chaos Theory through the Lyapunov Exponents and the Entropy of a Circuit to analytically estimate the effects caused by the variability of the manufacturing process, resulting in a method that can estimate the variability to Power, Delay, and Power Delay Product (PDP) with an accuracy equivalent to simulation-based methods, but on average three hundred times faster.
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